Small businesses can use Big Data to their advantage in an increasing number of ways. First, we'll see how data mining trends and distilling the information has made it possible for small businesses to identify problems that they could not before. Then we will look at concrete examples of how big data is used to solve these problems. Lastly, we will discuss how this technology allows for more efficient marketing channel management.

Data Mining

Data mining trends have given us a better understanding of consumer behavior by identifying customer patterns and calculating probabilities, which significantly increases our ability to make informed decisions. For example, through data mining methods such as clustering (grouping closely related things together) or classification (creating lists based on predetermined criteria), businesses can have more information on what type of people are looking to purchase their goods. With this information, businesses can apply data mining methods to target desired demographics with tailored messages that resonate more effectively with the customer base. This is crucial in today's society, where information is widely available on all products and services and RemoteDBA.com can help.

Clustering can also be used for identifying commonalities between large groups of customers, which allows marketers to pinpoint how they should interact with each group. Data mining can further benefit small businesses by identifying trends among competitors' marketing strategies, giving small businesses more insight into successful marketing ideas currently being executed by other companies in the same market space.

These are just some of how big data has contributed to an increase in revenue and the success of small businesses.

Marketing Channel Management

Small businesses can also utilize data mining trends to make better marketing decisions by efficiently managing their available channels. For example, it has become more effective to sequence sales efforts through multiple channels rather than trying to push a product on people at one specific time (see figurByhrough analyzing the customer's shopping behavior, marketers can pinpoint is best to reach them via certain channels such as email or direct comparison to alternative marketing methods such as television advertisements. This way, businesses spend less time and money sending out useless advertisements while increasing their likelihood of reaching potential customers and closing deals.
This approach has not only saved companies more than $1 billion annually. Still, it has also enhanced its ability for small businesses to reach customers at the right moment and subsequently generate more revenue.

Although these applications for big data are likely to not become fully operational until the near future, we can see how it will benefit many small businesses that cannot afford expensive marketing and advertising campaigns. While it is still hard to tell if the ratio of success among small and large companies will reflect that of similar industries in developing markets or developed markets, one thing is clear: business owners need to keep an eye out on this amazing technology because its role will be important in driving their organization's competitive advantage.

Small businesses in the United States are commercial enterprises with fewer than 500 employees.
Currently, the small business employs half of all private-sector workers and accounts for 53% of net new jobs in the US. While many businesses began using data in the 1980s to track sales, inventory levels, production output, and shipments -- it wasn't until the mid-to-late 1990s that managers started access to daily or hourly information. By 1997, most major corporations were utilizing some form of data analytics to make decisions regarding mergers & acquisitions (M&A) activity. Specifically, the dot-com boom caused a massive surge in venture capital investments -- allowing entrepreneurs to have unprecedented access to high-value datasets within an affordable budget.

The problem with small businesses is that many rely on manual or spreadsheets to store and crunch data. Additionally, they don't have the budget to hire a team of data scientists to perform sophisticated analysis -- which can result in missed opportunities and sparse insight into their core business problems. With the growth of cloud computing and Big Data technologies, smaller organizations can effectively compete against larger corporations by leveraging BI software, predictive analytics tools, social media monitoring applications, and web-scraping services on Amazon Web Services (AWS).

The evolution of small businesses & big data into Big Data Analytics

For companies to identify new opportunities, they need access to enough relevant data points and formulate an accurate narrative of their industry(s). Big data analytics platforms offer insight into historical trends and can turn data streams into actionable intelligence that can provide near real-time insights about competitors' strategies and customer preferences.

Facebook users upload over 300 million images on Facebook each day, which provides a treasure trove of visual data. For example, looking at photographs of cars within the Facebook feed might reveal insights about emerging trends in automobile sales. Moreover, by identifying multiple pictures of SUVs with expired license plates, auto industry analysts could conclude that car owners hold onto their older models for longer periods to avoid costly registration and insurance fees.

Additionally, big data analysis can identify customer purchasing patterns -- which are valuable information for marketers who want to find opportunities to sell additional products or services to existing customers. Big Data analytics companies such as PredicSis use nonlinear mathematical techniques such as artificial intelligence (AI) and machine learning algorithms to determine relationships between multiple variables and provide accurate forecasts.
Businesses apply predictive analytics across various fields that can significantly improve marketing, product development/management, financial modeling, customer service, and IT functions. The important thing to remember is that Big Data enables companies to obtain accurate insights about the world around them to make proactive decisions rather than reactive ones.

The downside to big data analytics & small businesses

While business owners are excited about leveraging Big Data for insight -- they should be aware of potential disadvantages related to technology implementation. For example, according to an Aberdeen Group study, only 28% of organizations had access to or owned Big Data in 2010.
Since then, this number has doubled (57%), but many companies still struggle with managing the sheer volume of information created each day, resulting in overwhelming storage costs and IT.